Adaptive Refinement Tree - A New High-Resolution N-Body Code for Cosmological Simulations,
Abstract
We present a new high-resolution N-body algorithm for cosmological simulations. The algorithm employs a traditional particle-mesh technique on a cubic grid and successive multilevel relaxations on the finer meshes, introduced recursively in a fully adaptive manner in the regions where the density exceeds a predefined threshold. The mesh is generated to effectively match an arbitrary geometry of the underlying density field-a property particularly important for cosmological simulations. In a simulation the mesh structure is not created at every time step but properly adjusted to the evolving particle distribution. The algorithm is fast and effectively parallel: the gravitational relaxation solver is approximately two times slower than the FFT solver on the same number of mesh cells. The required CPU time scales with number of cells, N suc c, as ^O(Nc). It allows us to improve considerably the spatial resolution of the particle-mesh code without loss in mass resolution. We present a detailed description of the methodology, implementation, and tests of the code. We further use the code to study the structure of dark matter halos in high-resolution (^2/h kpc) simulations of standard CDM (Omega = 1, h = 0.5, sigma sub g = 0.63) and (Lambda)CDM (0A = 1 -Omega sub O = 0.7, h = 0.7, sigma sub g = 1.0) models. We find that halo density profiles in both CDM and ACDM models are well fit by the analytical model presented recently by Navarro et al. (1966) which predicts a singular (rho(r) oc 1/r) behavior of the halo density profiles at small radii. We therefore conclude that halos formed in the (Lambda)CDM model have structure similar to the CDM halos, and thus cannot explain dynamics of the central parts of dwarf spiral galaxies infrerred from their rotation curves.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 28, 1997
- Accession Number
- ADA322030
Entities
People
- Alexei M. Khokhlovq
- Anatoly A. Klypin
- Andrey V. Kravtsov
Organizations
- United States Naval Research Laboratory